Advertisement

Journal of Meteorological Research

, Volume 33, Issue 5, pp 810–825 | Cite as

A Novel Identification of the Polar/Eurasia Pattern and Its Weather Impact in May

  • Ni Gao
  • Cholaw BuehEmail author
  • Zuowei Xie
  • Yuanfa Gong
Regular Article
  • 2 Downloads

Abstract

The Polar/Eurasia (POL) pattern was previously identified based on the empirical orthogonal function method and monthly mean data, in which the positive and negative phases are anti-symmetric in spatial distribution. This paper identifies the positive (POL+) and negative (POL) phases of the POL pattern through applying a novel approach, i.e., self-organizing maps, to daily 500-hPa geopotential height fields in May over 1948–2017. The POL+, POL1, and POL2 patterns defined by this method represent actual physical modes. The POL+ pattern features a wave train from the northeastern Atlantic/northern Europe via the subarctic regions of Eurasia to Lake Baikal. The POL1 pattern is characterized by a planetary-scale dipole pattern with a positive anomaly band over subarctic Eurasia and a negative anomaly band from central Asia to the Sea of Okhotsk. The anomaly centers of the POL2 pattern are basically anti-symmetrical to those of the POL+ pattern. The POL+ pattern increases the blocking frequency over the northeastern Atlantic/northern Europe and northeastern Asia, where high-frequency transient eddies are highly recurrent in the north. Accordingly, precipitation increases apparently in the subarctic Asian continent and western Siberia, and decreases around Europe and Lake Baikal. A mimic wave train is also observed in the surface air temperature anomaly field. During the POL1 period, the blocking frequency is abnormally high over Eurasia, whereas high-frequency transient eddies are apparently suppressed over northern Eurasia. Correspondingly, significant precipitation deficits are observed in northern Eurasia. The POL1 pattern also causes a remarkable temperature increase in the subarctic seas of Eurasia and a considerable temperature drop in the midlatitude Asian continent. As the POL2 pattern prevails, the blocking frequency decreases over the North Atlantic/Europe but strengthens over the Asian continent. The POL2 pattern also causes wavelike anomalies of precipitation and surface air temperature over northern Eurasia.

Key words

Polar/Eurasia (POL) pattern self-organizing maps blocking transient eddy 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgments

We thank the writers of NCARG Command Language (UCAR/NCAR/CISL/TDD 2017), which was used to plot the figures in this paper.

References

  1. Angell, J. K., 2006: Changes in the 300-mb north circumpolar vortex, 1963–2001. J. Climate, 19, 2984–2994, doi:  https://doi.org/10.1175/JCLI3778.1.CrossRefGoogle Scholar
  2. Balling, R. C. Jr., and G. B. Goodrich, 2011: Interannual variations in the local spatial autocorrelation of tropospheric temperatures. Theor. Appl. Climatol., 103, 451–457, doi:  https://doi.org/10.1007/s00704-010-0313-8.CrossRefGoogle Scholar
  3. Bao, M., and J. M. Wallace, 2015: Cluster analysis of Northern Hemisphere wintertime 500-hPa flow regimes during 1920–2014. J. Atmos. Sci., 72, 3597–3608, doi:  https://doi.org/10.1175/JAS-D-15-0001.1.CrossRefGoogle Scholar
  4. Barnston, A. G., and R. E. Livezey, 1987: Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Mon. Wea. Rev., 115, 1083–1126, doi:  https://doi.org/10.1175/1520-0493(1987)115<1083:CSAPOL>2.0.CO;2.CrossRefGoogle Scholar
  5. Bekryaev, R. V., I. V. Polyakov, and V. A. Alexeev, 2010: Role of polar amplification in long-term surface air temperature variations and modern Arctic warming. J. Climate, 23, 3888–3906, doi:  https://doi.org/10.1175/2010JCLI3297.1.CrossRefGoogle Scholar
  6. Bengtsson, L., K. I. Hodges, and E. Roeckner, 2006: Storm tracks and climate change. J. Climate, 19, 3518–3543, doi:  https://doi.org/10.1175/JCLI3815.1.CrossRefGoogle Scholar
  7. Bjerknes, J., 1969: Atmospheric teleconnections from the equatorial Pacific. Mon. Wea. Rev., 97, 163–172, doi:  https://doi.org/10.1175/1520-0493(1969)097<0163:ATFTEP>2.3.CO;2.CrossRefGoogle Scholar
  8. Bueh, C., and Z. W. Xie, 2015: An objective technique for detecting large-scale tilted ridges and troughs and its application to an East Asian cold event. Mon. Wea. Rev., 143, 4765–4783, doi:  https://doi.org/10.1175/MWR-D-14-00238.1.CrossRefGoogle Scholar
  9. Bueh, C., X. Y. Fu, and Z. W. Xie, 2011a: Large-scale circulation features typical of wintertime extensive and persistent low temperature events in China. Atmos. Ocean. Sci. Lett., 4, 235–241, doi:  https://doi.org/10.1080/16742834.2011.11446935.CrossRefGoogle Scholar
  10. Bueh, C., N. Shi, and Z. W. Xie, 2011b: Large-scale circulation anomalies associated with persistent low temperature over Southern China in January 2008. Atmos. Sci. Lett., 12, 273–280, doi:  https://doi.org/10.1002/asl.333.CrossRefGoogle Scholar
  11. Bueh, C., Y. Li, D. W. Lin, et al., 2016: Interannual variability of summer rainfall over the northern part of China and the related circulation features. J. Meteor. Res., 30, 615–630, doi:  https://doi.org/10.1007/s13351-016-5111-5.CrossRefGoogle Scholar
  12. Cai, M., and M. Mak, 1990: Symbiotic relation between planetary and synoptic-scale waves. J. Atmos. Sci., 47, 2953–2968, doi:  https://doi.org/10.1175/1520-0469(1990)047<2953:SRBPAS>2.0.CO;2.CrossRefGoogle Scholar
  13. Cavazos, T., 1999: Large-scale circulation anomalies conducive to extreme precipitation events and derivation of daily rainfall in Northeastern Mexico and Southeastern Texas. J. Climate, 12, 1506–1523, doi:  https://doi.org/10.1175/1520-0442(1999)012<1506:LSCACT>2.0.CO;2.CrossRefGoogle Scholar
  14. Chen, D., C. Bueh, and K. Y. Zhu, 2013: Interannual and interdecadal variabilities of circulation over Lake Baikal region in late spring and their association with temperature and precipitation over China. Chinese J. Atmos. Sci., 37, 1199–1209, doi:  https://doi.org/10.3878/j.issn.1006-9895.2012.12155. (in Chinese)Google Scholar
  15. Dai, P. X., and B. K. Tan, 2017: The nature of the Arctic Oscillation and diversity of the extreme surface weather anomalies it generates. J. Climate, 30, 5563–5584, doi:  https://doi.org/10.1175/JCLI-D-16-0467.1.CrossRefGoogle Scholar
  16. Esbensen, S. K., 1984: A comparison of intermonthly and interannual teleconnections in the 700 mb geopotential height field during the Northern Hemisphere winter. Mon. Wea. Rev., 112, 2016–2032, doi:  https://doi.org/10.1175/1520-0493(1984)112<2016:ACOIAI>2.0.CO;2.CrossRefGoogle Scholar
  17. Feldstein, S. B., and S. Lee, 2014: Intraseasonal and interdecadal jet shifts in the Northern Hemisphere: The role of warm pool tropical convection and sea ice. J. Climate, 27, 6497–6518, doi:  https://doi.org/10.1175/JCLI-D-14-00057.1.CrossRefGoogle Scholar
  18. Franzke, C., and S. B. Feldstein, 2005: The continuum and dynamics of Northern Hemisphere teleconnection patterns. J. Atmos. Sci., 62, 3250–3267, doi:  https://doi.org/10.1175/JAS3536.1.CrossRefGoogle Scholar
  19. Frauenfeld, O. W., and R. E. Davis, 2003: Northern Hemisphere circumpolar vortex trends and climate change implications. J. Geophys. Res. Atmos., 108, 4423, doi:  https://doi.org/10.1029/2002JD002958.CrossRefGoogle Scholar
  20. Gong, D. Y., and C. H. Ho, 2003: Arctic oscillation signals in the East Asian summer monsoon. J. Geophys. Res. Atmos., 108, 4066, doi:  https://doi.org/10.1029/2002JD002193.CrossRefGoogle Scholar
  21. Goss, M., S. B. Feldstein, and S. Lee, 2016: Stationary wave interference and its relation to tropical convection and Arctic warming. J. Climate, 29, 1369–1389, doi:  https://doi.org/10.1175/JCLI-D-15-0267.1.CrossRefGoogle Scholar
  22. He, J., and R. X. Black, 2016: Heat budget analysis of Northern Hemisphere high-latitude spring onset events. J. Geophys. Res. Atmos., 121, 10113–10137, doi:  https://doi.org/10.1002/2015JD024681.CrossRefGoogle Scholar
  23. Horel, J. D., 1981: A rotated principal component analysis of the interannual variability of the Northern Hemisphere 500 mb height field. Mon. Wea. Rev., 109, 2080–2092, doi:  https://doi.org/10.1175/1520-0493(1981)109<2080:ARPCAO>2.0.CO;2.CrossRefGoogle Scholar
  24. Hoskins, B. J., and K. I. Hodges, 2002: New perspectives on the Northern Hemisphere winter storm tracks. J. Atmos. Sci., 59, 1041–1061, doi:  https://doi.org/10.1175/1520-0469(2002)059<1041:NPOTNH>2.0.CO;2.CrossRefGoogle Scholar
  25. Hoskins, B. J., M. E. McIntyre, and A. W. Robertson, 1985: On the use and significance of isentropic potential vorticity maps. Quart. J. Roy. Meteor. Soc., 111, 877–946, doi:  https://doi.org/10.1256/smsqj.47001.CrossRefGoogle Scholar
  26. Hsu, H. H., and J. M. Wallace, 1985: Vertical structure of wintertime teleconnection patterns. J. Atmos. Sci., 42, 1693–1710, doi:  https://doi.org/10.1175/552-0469(1998)042<1693:VSOWTP>2.0.CO;2.CrossRefGoogle Scholar
  27. Hurrell, J. W., 1996: Influence of variations in extratropical wintertime teleconnections on Northern Hemisphere temperature. Geophys. Res. Lett, 23, 665–668, doi:  https://doi.org/10.1029/96GL00459.CrossRefGoogle Scholar
  28. Johnson, N. C., 2013: How many ENSO flavors can we distinguish? J. Climate, 26, 4816–4827, doi:  https://doi.org/10.1175/JCLI-D-12-00649.1.CrossRefGoogle Scholar
  29. Johnson, N. C., and S. B. Feldstein, 2010: The continuum of North Pacific sea level pressure patterns: Intraseasonal, interannual, and interdecadal variability. J. Climate, 23, 851–867, doi:  https://doi.org/10.1175/2009JCLI3099.1.CrossRefGoogle Scholar
  30. Johnson, N. C., S. B. Feldstein, and B. Tremblay, 2008: The continuum of Northern Hemisphere teleconnection patterns and a description of the NAO shift with the use of self-organizing maps. J. Climate, 21, 6354–6371, doi:  https://doi.org/10.1175/2008JCLI2380.1.CrossRefGoogle Scholar
  31. Kalnay, E., M. Kanamitsu, R. Kistler, et al., 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437–472, doi:  https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.CrossRefGoogle Scholar
  32. Kohonen, T., 1990: The self-organizing map. Proc. IEEE, 78, 1464–1480, doi:  https://doi.org/10.1109/5.58325.CrossRefGoogle Scholar
  33. Kohonen, T., 1997: Self-Organizing Maps. Springer-Verlag, Berlin, Heidelberg, 426 pp.CrossRefGoogle Scholar
  34. Kushnir, Y., and J. M. Wallace, 1989: Low-frequency variability in the Northern Hemisphere winter: Geographical distribution, structure and time-scale dependence. J. Atmos. Sci., 46, 3122–3143, doi:  https://doi.org/10.1175/1520-0469(1989)046<3122:LFVTTN>2.0.CO;2.CrossRefGoogle Scholar
  35. Lee, M. H., S. Lee, H. J. Song, et al., 2017: The recent increase in the occurrence of a boreal summer teleconnection and its relationship with temperature extremes. J. Climate, 30, 7493–7504, doi:  https://doi.org/10.1175/JCLI-D-16-0094.1.CrossRefGoogle Scholar
  36. Lee, S., and S. B. Feldstein, 2013: Detecting ozone- and greenhouse gas-driven wind trends with observational data. Science, 339, 563–567, doi:  https://doi.org/10.1126/science.1225154.CrossRefGoogle Scholar
  37. Lehmann, J., D. Coumou, K. Frieler, et al., 2014: Future changes in extratropical storm tracks and baroclinicity under climate change. Environ. Res. Lett., 9, 084002, doi:  https://doi.org/10.1088/1748-9326/9/8/084002.CrossRefGoogle Scholar
  38. L’Heureux, M. L., D. C. Collins, and Z. Z. Hu, 2013: Linear trends in sea surface temperature of the tropical Pacific Ocean and implications for the El Niño-Southern Oscillation. Climate Dyn., 40, 1223–1236, doi:  https://doi.org/10.1007/s00382-012-1331-2.CrossRefGoogle Scholar
  39. Lin, Z. D., 2014: Intercomparison of the impacts of four summer teleconnections over Eurasia on East Asian rainfall. Adv. Atmos. Sci., 31, 1366–1376, doi:  https://doi.org/10.1007/s00376-014-3171-y.CrossRefGoogle Scholar
  40. Lin, Z. D., and B. Wang, 2016: Northern East Asian low and its impact on the interannual variation of East Asian summer rainfall. Climate Dyn., 46, 83–97, doi:  https://doi.org/10.1007/s00382-015-2570-9.CrossRefGoogle Scholar
  41. Liu, Y. G., R. H. Weisberg, and C. N. K. Mooers, 2006: Performance evaluation of the self-organizing map for feature extraction. J. Geophys. Res. Oceans, 111, C05018, doi:  https://doi.org/10.1029/2005JC003117.CrossRefGoogle Scholar
  42. Nakamura, H., M. Nakamura, and J. L. Anderson, 1997: The role of high- and low-frequency dynamics in blocking formation. Mon. Wea. Rev., 125, 2074–2093, doi:  https://doi.org/10.1175/1520-0493(1997)125<2074:TROHAL>2.0.CO;2.CrossRefGoogle Scholar
  43. Pelly, J. L., and B. J. Hoskins, 2003: A new perspective on blocking. J. Atmos. Sci., 60, 743–755, doi:  https://doi.org/10.1175/1520-0469(2003)060<0743:ANPOB>2.0.CO;2.CrossRefGoogle Scholar
  44. Piao, J. L., W. Chen, S. F. Chen, et al., 2018: Intensified impact of North Atlantic Oscillation in May on subsequent July Asian inland plateau precipitation since the late 1970s. Int. J. Climatol., 38, 2605–2612, doi:  https://doi.org/10.1002/joc.5332.CrossRefGoogle Scholar
  45. Reusch, D. B., R. B. Alley, and B. C. Hewitson, 2007: North Atlantic climate variability from a self-organizing map perspective. J. Geophys. Res. Atmos., 112, D02104, doi:  https://doi.org/10.1029/2006JD007460.CrossRefGoogle Scholar
  46. Rousi, E., C. Anagnostopoulou, K. Tolika, et al., 2015: Representing teleconnection patterns over Europe: A comparison of SOM and PCA methods. Atmos. Res., 152, 123–137, doi:  https://doi.org/10.1016/j.atmosres.2013.11.010.CrossRefGoogle Scholar
  47. Sheridan, S. C., and C. C. Lee, 2011: The self-organizing map in synoptic climatological research. Prog. Phys. Geogr., 35, 109–119, doi:  https://doi.org/10.1177/0309133310397582.CrossRefGoogle Scholar
  48. Tan, B. K., and W. Chen, 2014: Progress in the study of the dynamics of extratropical atmospheric teleconnection patterns and their impacts on East Asian climate. J. Meteor. Res., 28, 780–802, doi:  https://doi.org/10.1007/s13351-014-4041-3.CrossRefGoogle Scholar
  49. Wallace, J. M., and D. S. Gutzler, 1981: Teleconnections in the geopotential height field during the Northern Hemisphere winter. Mon. Wea. Rev., 109, 784–812, doi:  https://doi.org/10.1175/1520-0493(1981)109<0784:TITGHF>2.0.CO;2.CrossRefGoogle Scholar
  50. Ward, J. H. Jr., 1963: Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc., 58, 236–244, doi:  https://doi.org/10.2307/2282967.CrossRefGoogle Scholar
  51. Xie, Z., R. X. Black, and Y. Deng, 2017: Daily-scale planetary wave patterns and the modulation of cold season weather in the northern extratropics. J. Geophys. Res. Atmos., 122, 8383–8398, doi:  https://doi.org/10.1002/2017JD026768.CrossRefGoogle Scholar
  52. Xie, Z. W., and C. Bueh, 2017a: Cold vortex events over Northeast China associated with the Yakutsk-Okhotsk blocking. Int. J. Climatol., 37, 381–398, doi:  https://doi.org/10.1002/joc.4711.CrossRefGoogle Scholar
  53. Xie, Z. W., and C. Bueh, 2017b: Blocking features for two types of cold events in East Asia. J. Meteor. Res., 31, 309–320, doi:  https://doi.org/10.1007/s13351-017-6076-8.CrossRefGoogle Scholar
  54. Xu, G. D., Y. Zong, and Z. L. Yang, 2013: Applied Data Mining. CRC Press, Inc., Boca Raton, FL, USA, 284 pp.CrossRefGoogle Scholar
  55. Yatagai, A., K. Kamiguchi, O. Arakawa, et al., 2012: APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull. Amer. Meteor. Soc., 93, 1401–1415, doi:  https://doi.org/10.1175/BAMS-D-11-00122.1.CrossRefGoogle Scholar
  56. Ye, H. C., E. J. Fetzer, A. Behrangi, et al., 2016: Increasing daily precipitation intensity associated with warmer air temperatures over northern Eurasia. J. Climate, 29, 623–636, doi:  https://doi.org/10.1175/JCLI-D-14-00771.1.CrossRefGoogle Scholar
  57. Yeh, T. C., S. Y. Dao, and M. T. Li, 1958: The abrupt change of circulation over Northern Hemisphere during June and October. Acta Meteor. Sinica, 29, 249–263. (in Chinese)Google Scholar
  58. Yuan, J. C., B. K. Tan, S. B. Feldstein, et al., 2015: Wintertime North Pacific teleconnection patterns: Seasonal and interannual variability. J. Climate, 28, 8247–8263, doi:  https://doi.org/10.1175/JCLI-D-14-00749.1.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2019

Authors and Affiliations

  1. 1.College of Atmosphere ScienceChengdu University of Information TechnologyChengduChina
  2. 2.International Center for Climate and Environment Sciences, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina

Personalised recommendations